• Title/Summary/Keyword: Wavelet transform

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Noise Suppression in NMR Spectrum by Using Wavelet Transform Analysis

  • Kim, Daesung;Youngdo Won;Hoshik Won
    • Journal of the Korean Magnetic Resonance Society
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    • v.4 no.2
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    • pp.103-115
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    • 2000
  • Wavelet transforms are introduced as a new tool to distinguish real peaks from the noise contaminated NMR data in this paper. New algorithms of two wavelet transforms including Daubechies wavelet transform as a discrete and orthogonal wavelet transform (DWT) and Morlet wavelet transform as a continuous and nonorthogonal wavelet transform(CWT) were developed fer noise elimination. DWT and CWT method were successfully applied to the noise reduction in spectrum. The inevitable distortion of NMR spectral baseline and the imperfection in noise elimination were observed in DWT method while CWT method gives a better baseline ahape and a well noise suppressed spectrum.

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A Study on Denoising Methods using Wavelet in AWGN environment (AWGN 환경에서 웨이브렛을 이용한 잡음 제거 방법에 관한 연구)

  • 배상범;김남호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.5
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    • pp.853-860
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    • 2001
  • This paper presents the new two denoising methods using wavelet. One is new spatially selective noise filtration(NSSNF) using spatial correlation and the other is undecimated discrete wavelet transform (UDWT) threshold-based. NSSNF got the flexible gain special property of SNR adding new parameter at the existing SSNF and UDWT had superior denosing effect than orthogonal wavelet transform(OWT) applied soft-threshold by applied hard-threshold. We selected additive white gaussian noise(AWGN) in this test environment. Also we analyzed and compared ousting denoising method using SNR as standard of judgement of improvemental effect.

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Retrieval of Key-frames using Wavelet Transform (Wavelet Transform을 이용한 Key-frame 검색)

  • 정세윤;김규헌;전병태;이재연;배영래
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.509-511
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    • 1998
  • 본 논문에서는 동영상 데이터베이스에서 Key-frame을 검색하는 방법을 제안한다. 본 논문에서는 Key-frame을 검색하기위해 컬러 피쳐를 공간영역에서 추출하지 않고 wavelet transform 영역에서 컬러 피쳐를 추출하는 방법을 제안한다. wavelet transform 의 저주파 밴드는 영상전체의 특징을 잘 나타내고 고주파 밴드는 texture 와 국부적인 컬러 특성을 잘 나타낸다. 색인과정 알고리즘은 영상의 크기를 정규화하고 RGB 컬러공간에서 HSV 컬러 공간으로 변환을 하여, H, S, V 각 채널에 대해 Daubechies' wavelet transform을 수행한 후 변환 영역에서 피쳐를 추출하게 된다. 색인을 위한 피쳐로 wavelet 계수와 lowest 밴드의 평균과 표준편차를 추출하였다. 효율적인 검색을 위해 검색은 2단계로 수행된다. 먼저 평균과 표준편차만을 이용한 1차 검색을 통해 2차 검색의 후보 영상들을 추출하고 2차 검색에서는 1차 검색 통과 영상들에 대해서만 wavelet 계수들을 비교하여 최종 검색 결과를 얻게 된다. 검색결과 기존의 컬러 피쳐를 이용한 방법보다 우수한 검색결과를 얻을 수 있었다.

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Analysis of 2-Dimensional Object Recognition Using discrete Wavelet Transform (이산 웨이브렛 변환을 이용한 2차원 물체 인식에 관한 연구)

  • Park, Kwang-Ho;Kim, Chang-Gu;Kee, Chang-Doo
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.10
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    • pp.194-202
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    • 1999
  • A method for pattern recognition based on wavelet transform is proposed in this paper. The boundary of the object to be recognized includes shape information for object of machine parts. The contour is first represented using a one-dimensional signal and normalized about translation, rotation and scale, then is used to build the wavelet transform representation of the object. Wavelets allow us to decompose a function into multi-resolution hierarchy of localized frequency bands. The recognition of 2-dimensional object based on the wavelet is described to analyze the shape of analysis technique; the discrete wavelet transform(DWT). The feature vectors obtained using wavelet analysis is classified using a multi-layer neural network. The results show that, compared with the use of fourier descriptors, recognition using wavelet is more stable and efficient representation. And particularly the performance for objects corrupted with noise is better than that of other method.

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Dynamic Filtering of End-milling Force Using Wavelet Filter Bank (웨이블렛 필터뱅크를 이용한 동적 엔드밀 절삭력 필터링)

  • Cho, Hee-Geun;Chin, Do-Hun;Yoon, Moon-Chul
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.18 no.4
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    • pp.381-387
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    • 2009
  • The end-milling force behaviour is very complex and it is related to a de-noising phenomenon, so it is very difficult to detect and diagnose this static cutting force phenomenon. This paper presents a new method of filtering of end-milling force in end-milling operation using filter bank technique, based on the wavelet transform. In this paper by comparing the history of end-milling force using wavelet filtering the fundamental end-milling property of the wavelet transform is well reviewed and analyzed. This result of wavelet transform using filter bank shows the possible static prediction of end-milling force with severe dynamic properties such as chatter in end-milling operation.

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Application of Envelop Analysis and Wavelet Transform for Detection of Gear Failure (기어 결함 검출을 위한 포락처리와 웨이블릿 변환의 적용)

  • Gu, Dong-Sik;Lee, Jeong-Hwan;Yang, Bo-Suk;Choi, Byeong-Keun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.32 no.11
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    • pp.905-910
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    • 2008
  • Vibration analysis is widely used in machinery diagnosis and the wavelet transform has also been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether acoustic signal can be used effectively along vibration signal to detect the various local fault, in local fault of gearboxes using the wavelet transform. Moreover, envelop analysis is well known as useful tool for the detection of rolling element bearing fault. In this paper, a acoustic emission (AE) sensor is employed to detect gearbox damage by installing them around bearing housing at driven-end side. Signal processing is conducted by wavelet transform and enveloping to detect her fault all at once gearbox using AE signal.

Identification of Mass-Lines and Rigid Body Properties using Wavelet Transform (웨이블렛 변환을 이용한 질량선 및 강체특성의 규명)

  • 안세진;정의봉;황대선
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.05a
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    • pp.115-120
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    • 2002
  • The rigid body properties of a structure may be estimated easily if the mass-line of the structure could be taken exactly. However, the exact mass-line may be hard to be obtained exactly in experiments. The mass line value can be read from the mass line in frequency response function. However, the mass lines in the frequency response function sometimes show the fluctuation with frequency, and it cannot be read correctly. In this paper, the wavelet transform is applied to obtain the good mass line value. The mass line calculated by using wavelet transform has unique value and showed in the range of fluctuated values of frequency response function. The rigid body properties obtained by wavelet transform also showed better results than those by fourier transform.

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A Study on the Comparison of Denoising Performance of Stationary Wavelet Transform for Discharge Signal Data in Cast-resin Transformer (SWT(Stationary Wavelet Transform)를 이용한 몰드변압기 방전 측정신호의 디노이징 특성 연구)

  • Choi, Myeong-Il;Kim, Jae-Chul
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.3
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    • pp.84-90
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    • 2014
  • The partial discharge of Cast-resin Transformer has a difficulty to be analyzed, because it is an abnormal condition signal of which stochastic characteristics varies with time variance. In this study, background noise coming from the outside of the cast-resin transformers through ground wire can be removed and only a discharge signal of which defects are simulated can be obtained, using the wavelet transform method, which is a time-frequency domain analysis technique. As a result, it was confirmed that de-noising using the SWT technique is the best efficient among three methods of the wavelet transform techniques.

Image Cryptographic Algorithm Based on the Property of Wavelet Packet Transform (웨이브렛 패킷 변환의 특성을 이용한 영상 암호화 알고리즘)

  • Shin, Jonghong
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.14 no.2
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    • pp.49-59
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    • 2018
  • Encryption of digital images has been requested various fields. In the meantime, many algorithms based on a text - based encryption algorithm have been proposed. In this paper, we propose a method of encryption in wavelet transform domain to utilize the characteristics of digital image. In particular, wavelet transform is used to reduce the association between the encrypted image and the original image. Wavelet packet transformations can be decomposed into more subband images than wavelet transform, and various position permutation, numerical transformation, and visual transformation are performed on the coefficients of this subband image. As a result, this paper proposes a method that satisfies the characteristics of high encryption strength than the conventional wavelet transform and reversibility. This method also satisfies the lossless symmetric key encryption and decryption algorithm. The performance of the proposed method is confirmed by visual and quantitative. Experimental results show that the visually encrypted image is seen as a completely different signal from the original image. We also confirmed that the proposed method shows lower values of cross correlation than conventional wavelet transform. And PSNR has a sufficiently high value in terms of decoding performance of the proposed method. In this paper, we also proposed that the degree of correlation of the encrypted image can be controlled by adjusting the number of wavelet transform steps according to the characteristics of the image.

Application of Technique Discrete Wavelet Transform for Acoustic Emission Signals (음향방출신호에 대한 이산웨이블릿 변환기법의 적용)

  • 박재준;김면수;김민수;김진승;백관현;송영철;김성홍;권동진
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2000.07a
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    • pp.585-591
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    • 2000
  • The wavelet transform is the most recent technique for processing signals with time-varying spectra. In this paper, the wavelet transform is utilized to improved the assessment and multi-resolution analysis of acoustic emission signals generating in partial discharge. This paper especially deals with the assessment of process statistical parameter using the features extracted from the wavelet coefficients of measured acoustic emission signals in case of applied voltage 20[kv]. Since the parameter assessment using all wavelet coefficients will often turn out leads to inefficient or inaccurate results, we selected that level-3 stage of multi decomposition in discrete wavelet transform. We applied FIR(Finite Impulse Response)digital filter algorithm in discrete to suppression for random noise. The white noise be included high frequency component denoised as decomposition of discrete wavelet transform level-3. We make use of the feature extraction parameter namely, maximum value of acoustic emission signal, average value, dispersion, skewness, kurtosis, etc. The effectiveness of this new method has been verified on ability a diagnosis transformer go through feature extraction in stage of acting(the early period, the last period) .

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